Fred Vermolen

Scopus Author ID ORCID

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 7

Top Topics

Machine Learning

Psychometric Properties

Top Venues

Journal of mathematical biology

Biomechanics and modeling in mechanobiology

Neural computing & applications

University of Hasselt

Delft University of Technology (PHD)

This page only lists publications with an associated author ORCID identifier.

Affiliation History

University of Hasselt May 01 2020

Belgium

Professor :: Computational Mathematics (CMAT)

Education History

Delft University of Technology May 01 1994 - May 28 1998

Netherlands

PHD :: Department of Applied Mathematics / Department of Materials Science

Delft University of Technology Delft Sep 01 1987 - Aug 20 1993

Netherlands

MSC :: Department of Applied Physics - Mathematical Physics

Publications

Ginger Egberts, Fred Vermolen, Paul van Zuijlen
Stability of a two-dimensional biomorphoelastic model for post-burn contraction. Journal of mathematical biology 86 (4) (2023)
Riham K Ahmed, Tamer Abdalrahman, Neil Hamer Davies, Fred Vermolen, Thomas Franz
Mathematical model of mechano-sensing and mechanically induced collective motility of cells on planar elastic substrates. Biomechanics and modeling in mechanobiology (2023)
Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen
A Bayesian finite-element trained machine learning approach for predicting post-burn contraction. Neural computing & applications 34 (11) (2022)
Ginger Egberts, Alexis Desmoulière, Fred Vermolen, Paul van Zuijlen
Sensitivity of a two-dimensional biomorphoelastic model for post-burn contraction. Biomechanics and modeling in mechanobiology (2022)
Ginger Egberts, Fred Vermolen, Paul van Zuijlen
Sensitivity and feasibility of a one-dimensional morphoelastic model for post-burn contraction. Biomechanics and modeling in mechanobiology 20 (6) (2021)
Ginger Egberts, Fred Vermolen, Paul van Zuijlen
Stability of a one-dimensional morphoelastic model for post-burn contraction. Journal of mathematical biology 83 (3) (2021)
Fred Vermolen, Ilkka Pölönen
Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer. Journal of mathematical biology 80 (3) (2019)